Skip to main content
Glama
asanm11611622ubca006

Patient Data MCP Server

🏥 Patient Data MCP Server

Welcome to the Patient Data MCP (Model Context Protocol) Server project! 🚀

This is a beginner-friendly project showing how to connect Claude Desktop to your own local Python data sources. It lets you chat with a synthetic patient dataset containing 200 health records. 🧑‍⚕️📊

If you are a student or developer wanting to learn how to bridge LLMs with real-world databases, this is a perfect starting point! 💡


🛠️ Features

This server currently provides 6 powerful tools to Claude:

  1. 🔍 get_patient_by_id — Look up a specific patient record.

  2. 🎂 list_patients_above_age — Find older patients based on an age threshold.

  3. 🦠 find_patients_by_disease — Search for patients by their diagnosis (e.g., Asthma, Diabetes).

  4. 📋 list_all_diseases — See all unique diseases present in the dataset.

  5. 👤 search_patients_by_name — Quickly find someone by their partial or full name.

  6. 📈 get_patient_statistics — Receive a beautiful statistical breakdown of the dataset.


Related MCP server: SQLite MCP Server

🖥️ Getting Started

1️⃣ Prerequisites

You will need a few things installed on your machine:

  • Python 3.10+ (🐍)

  • uv (⚡ A blazing fast Python package runner). Install it via terminal:

    • macOS/Linux: curl -LsSf https://astral.sh/uv/install.sh | sh

    • Windows: irm https://astral.sh/uv/install.ps1 | iex

  • Claude Desktop App (🤖)

2️⃣ Clone the Repository

Download the code to your computer:

git clone https://github.com/asanm11611622ubca006/First-MCP-server.git
cd First-MCP-server

(Optional) Run python generate_dataset.py if you ever want to regenerate the randomized patients.csv file!

3️⃣ Connect to Claude Desktop! 🔌

You don't need to run the server in your terminal. Claude will automatically run it in the background!

  1. Open your Claude Desktop config file:

    • Windows: %APPDATA%\Claude\claude_desktop_config.json

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  2. Add the following JSON configuration. Make sure to update the --directory path to where you saved the code on your computer!

{
  "mcpServers": {
    "patient-data-server": {
      "command": "uv",
      "args": [
        "--directory",
        "YOUR_FULL_PATH_HERE\\First_MCP_server", 
        "run",
        "patient_server.py"
      ]
    }
  }
}

(⚠️ Windows users: Remember to use double backslashes \\ in path names!)

4️⃣ Start Chatting! 💬

  1. Restart Claude Desktop (fully quit from the system tray and reopen).

  2. Look for the little 🔨 (Hammer) icon in the chat bar. You should see the patient-data-server features loaded!

  3. Try asking:

    • "What are the most common diseases in the patient database?"

    • "Can you find patients with Hypertension?"

    • "Get patient by ID 42"


🌱 Learning & Contributing

This project is an awesome way to learn how the Model Context Protocol works. You can easily open patient_server.py and modify it.

Try adding a new tool to find patients by gender, or swap out the CSV parsing for an SQL database! 👩‍💻👨‍💻

Happy coding! 🎉

F
license - not found
-
quality - not tested
D
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/asanm11611622ubca006/First-MCP-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server